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Alternative Methods for Solving the Problem of Selection Bias in Evaluating the Impact of Treatments on Outcomes

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Drawing Inferences from Self-Selected Samples

Abstract

Social scientists never have access to true experimental data of the type sometimes available to laboratory scientists.1 Our inability to use laboratory methods to independently vary treatments to eliminate or isolate spurious channels of causation places a fundamental limitation on the possibility of objective knowledge in the social sciences. In place of laboratory experimental variation, social scientists use subjective thought experiments. Assumptions replace data. In the jargon of modern econometrics, minimal identifying assumptions are invoked.

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Heckman, J.J., Robb, R. (1986). Alternative Methods for Solving the Problem of Selection Bias in Evaluating the Impact of Treatments on Outcomes. In: Wainer, H. (eds) Drawing Inferences from Self-Selected Samples. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-4976-4_7

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  • DOI: https://doi.org/10.1007/978-1-4612-4976-4_7

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4612-9381-1

  • Online ISBN: 978-1-4612-4976-4

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